MétaCan
Menu
Back to cohort
Record W2150581696 · doi:10.1109/cdc.1994.411195

Adaptive control of variable reluctance motors using spline functions

2002· article· en· W2150581696 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsControl theory (sociology)Switched reluctance motorTorqueCommutationDirect torque controlRotor (electric)Adaptive controlComputer scienceController (irrigation)Magnetic reluctancePID controllerControl engineeringSpline (mechanical)Electromagnetic coilEngineeringInduction motorControl (management)PhysicsVoltageArtificial intelligenceElectrical engineeringMagnetMechanical engineering

Abstract

fetched live from OpenAlex

Considers the model-reference adaptive control of a variable reluctance motor (VRM) for low-speed, high-torque operation. the authors use spline functions to model the VRM characteristic relating electric torque to rotor angular position and winding current. This model leads to a simple, computationally efficient, adaptive controller. The authors also incorporate "torque sharing functions" to smooth the electronic commutation between windings and to increase the peak torque available in the closed-loop (compared with "hard" commutation). The authors provide simulation results for a three-phase VRM that illustrate the design and performance of the adaptive controller.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.182
Teacher spread0.166 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations16
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicSensorless Control of Electric MotorsFrench-language works237,207